[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

src/litserve/specs/openai_embedding.py

@@ -146,7 +146,8 @@ def setup(self, server: "LitServer"):
 
     def _check_lit_api(self, api):
         from litserve import LitAPI
-        if isinstance(api.spec,OpenAIEmbeddingSpec):
+
+        if isinstance(api.spec, OpenAIEmbeddingSpec):
             if inspect.isgeneratorfunction(api.predict):
                 raise ValueError(
                     "You are using yield in your predict method, which is used for streaming.",

src/litserve/test_examples/openai_embedding_spec_example.py

@@ -16,6 +16,7 @@ def predict(self, x) -> List[List[float]]:
     def encode_response(self, output) -> dict:
         return {"embeddings": output}
 
+
 class TestOpenAPI(LitAPI):
     def setup(self, device):
         self.model = None
@@ -24,7 +25,7 @@ async def predict(self, x) -> List[List[float]]:
         n = len(x) if isinstance(x, list) else 1
         yield np.random.rand(n, 768).tolist()
 
-    async  def encode_response(self, output) -> dict:
+    async def encode_response(self, output) -> dict:
         yield {"embeddings": output}
 
 

tests/unit/test_openai_embedding.py

@@ -26,12 +26,12 @@
 from litserve.specs.openai_embedding import OpenAIEmbeddingSpec
 from litserve.test_examples.openai_embedding_spec_example import (
     TestEmbedAPI,
-    TestOpenAPI,
     TestEmbedAPIWithMissingEmbeddings,
     TestEmbedAPIWithNonDictOutput,
     TestEmbedAPIWithUsage,
     TestEmbedAPIWithYieldEncodeResponse,
     TestEmbedAPIWithYieldPredict,
+    TestOpenAPI,
 )
 from litserve.utils import wrap_litserve_start
 
@@ -52,11 +52,12 @@ async def test_openai_embedding_spec_with_single_input(openai_embedding_request_
             assert len(resp.json()["data"]) == 1, "Length of data should be 1"
             assert len(resp.json()["data"][0]["embedding"]) == 768, "Embedding length should be 768"
 
+
 @pytest.mark.asyncio
 async def test_openai_embedding_spec_with_multi_endpoint(openai_embedding_request_data):
     spec_openai = OpenAISpec()
     spec_embedding = OpenAIEmbeddingSpec()
-    server = ls.LitServer([TestOpenAPI(spec=spec_openai,enable_async=True),TestEmbedAPI(spec=spec_embedding)])
+    server = ls.LitServer([TestOpenAPI(spec=spec_openai, enable_async=True), TestEmbedAPI(spec=spec_embedding)])
     with wrap_litserve_start(server) as server:
         async with LifespanManager(server.app) as manager, AsyncClient(
             transport=ASGITransport(app=manager.app), base_url="http://test"